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Assoc Dir Statistical Programming in Bernards, NJ at DSI

Date Posted: 2/13/2019

Job Snapshot

Job Description

Job Summary:
The purpose of this job is to provide statistical programming technical support to DSI project teams on all statistical programming deliverables and programming submission. It will also improve Daiichi Sankyo programming efficiency by developing tools and macros and build up standard on SDTM/ADaM datasets, and TFLs.

  • Supporting project lead on outsourced projects, act as statistical programming subject matter expert (SME) to support outsourced programming activities and be responsible for the programming technical decision. By guiding other internal programmer or by self, perform programmatic review of Study Date Tabulation Model (SDTM) and analysis (including Analysis Data Model (ADaM)) datasets as well as TLFs generated by statistical vendor, ensure correct and effective vendor programming implementation, and expedite the preparation of regulatory submissions. Responsibilities include: make strategic programming decision and planning, review Case Report Form (CRF) annotation and SDTM dataset, identify data inconsistencies and support data review, review analysis dataset specifications and ensure correct interpretation of SAP, develop independent programs to validate stud level analysis dataset and TLFs generated by vendor, ensure analysis dataset in compliance with CDISC and submission requirement, review study submission data package and ensure its quality and integrity.
  • Provide hands-on statistical programming support to regulatory submission and help submission team in quick turnaround in response to regulatory agencies. Responsibilities include: develop programming submission strategy, perform integrated analysis of efficacy and safety, generate submission data package, create TLFs to support submission Q&As, perform ad-hoc and exploratory analysis requested by clinical team, and support agency response or potential Advisory Committee Meeting
  • Develop DSI programming standard template on datasets and TFLs to improve efficiency and quality. Responsibilities include: contribute to CRF and SDTM standard development, develop, implement, and maintain SDTM, ADaM dataset and TLF standard, develop sample programs to generate and validate SDTM, ADaM dataset and TLFs, support technical training and ensure effective implementation of SDTM, ADaM and TLFs standard in clinical trial data analysis
  • Develop and maintain necessary programming macros or tools to effectively support all programming needs. Responsibilities include: identify the macros or tools that will facilitate programing efficiency, lead the macro or tool development by working with contractors or by self, and support the macro or tool implementation and maintenance
  • Evaluate, assess and enhance DSI computing environment system. Responsibilities include: continue assessing DSI new computing environment system for programming and analysis efficiency, identify system bug/issue and lead the activity to enhance the system, develop system training materials and work as the SME to support implementation, evaluate, request and approve system upgrades, and propose/develop system utilities

Bachelor's degree from an accredited institution in a technical field such as computer science or mathematics; Master’s degree in biostatistics preferred
  • Minimum 10 years (or Master’s degree with minimum of 7 years) proven experience within pharmaceutical industry, or CROs supporting statistical analysis of clinical trials programming
  • Previous experience supporting SAS macro and/or system utility development is highly preferred
  • Advanced working knowledge of all aspects of the SAS programming language used in clinical trials programming
  • Advanced working knowledge of CDISC SDTM and ADaM, and extensive experiences of their implementation in clinical trials analysis
  • Advanced understanding of statistical concepts in support of analyses and reporting of clinical trials
  • Knowledge of all phases of drug development, including early and late phase clinical development and submission
  • Solid background in applied statistics
  • Solid knowledge of new advanced statistical methods using SAS and R
  • Advanced knowledge in database structures and set-up